CN108219826B - Control method of catalytic cracking device - Google Patents

Control method of catalytic cracking device Download PDF

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CN108219826B
CN108219826B CN201711441371.3A CN201711441371A CN108219826B CN 108219826 B CN108219826 B CN 108219826B CN 201711441371 A CN201711441371 A CN 201711441371A CN 108219826 B CN108219826 B CN 108219826B
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regenerator
coke content
catalytic cracking
cracking unit
temperature
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CN108219826A (en
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叶凌箭
沈非凡
王朗
李英道
马修水
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Ningbo Institute of Technology of ZJU
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    • C—CHEMISTRY; METALLURGY
    • C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
    • C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
    • C10G11/00—Catalytic cracking, in the absence of hydrogen, of hydrocarbon oils

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  • Organic Chemistry (AREA)
  • Production Of Liquid Hydrocarbon Mixture For Refining Petroleum (AREA)

Abstract

The invention provides a control method of a catalytic cracking unit, which comprises the following steps: determining controlled variables in the catalytic cracking unit, wherein the controlled variables are cyclone separator temperature and regenerator coke content; acquiring optimal set values corresponding to the temperature of the cyclone separator and the coke content of the regenerator based on a parameterized mathematical model of the catalytic cracking unit; acquiring a data set of an input variable and an output variable, establishing a prediction model of the coke content of the regenerator, and performing online prediction on the coke content of the regenerator; the feedback controller is used to perform on-line closed loop control of the cyclone temperature and the output of the software measurement model of regenerator coke content. The whole method is safe to operate and stable to operate, economic indexes are directly optimized to a great extent, and production benefits are effectively improved.

Description

Control method of catalytic cracking device
Technical Field
The invention relates to the field of catalytic cracking, in particular to a control method of a catalytic cracking device.
Background
The catalytic cracking unit is one of the core processes of the petroleum refining industry and is also one of the most technically difficult processes. How to use an automatic control theory and an optimization technology to carry out stable and efficient operation on a catalytic cracking device is an important proposition of an industrial automation technology. In a catalytic cracking unit, the oil feed is first mixed with the catalyst recovered from the regenerator and preheated, entering the riser for the cracking reaction. The high temperature regenerated catalyst provides the heat required for the gasification and reaction of the heavy oil. Stripping steam is introduced into the stripping section of the separator, and volatile gas-phase hydrocarbon products are separated from the catalyst and distilled out from the top. The by-product coke of the cracking reaction is attached to the surface of the catalyst, and the activity of the catalyst is reduced. The deactivated catalyst is conveyed to a regenerator, and oxygen-containing air is introduced into the regenerator to burn off carbon deposit and recover the activity of the catalyst. The top of the regenerator is provided with a cyclone separator for recovering the catalyst carried by the air, and the regenerated catalyst is mixed with the raw material and then enters the riser for recycling. The control and optimization aim is to design a reasonable control system, and the economic benefit of the device is improved on the basis of ensuring safe and stable operation of the process.
The control objectives of a catalytic cracker can be summarized in a number of ways, such as: (1) the reaction temperature and the regeneration temperature are stabilized, and the stable operation of the device is ensured; (2) the reaction depth is controlled, and the product yield is improved; (3) the oxygen content of the regenerated flue gas is controlled, and the air consumption of the device is reduced; (4) the potential of the device is excavated, the processing capacity is improved, and the economic benefit is increased. The control method and the control system of the catalytic cracking unit play an important role in achieving the above-mentioned objects. Under the background of market economy and globalization, the task of improving the economic benefit of a catalytic cracking unit and improving the competitiveness of enterprises by designing an efficient control system and an optimization method is particularly important. In the traditional method, a control system firstly realizes the safe operation and the stable operation of the device by optimizing a controller, controller parameters and other main modes to achieve the control target. On the basis, the optimal set value of the controlled variable needs to be further adjusted through advanced technologies such as online optimization and the like, so that the optimization of economic indexes is realized.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a control method of a catalytic cracking unit, which effectively improves the production benefit.
The technical scheme of the invention is as follows: a method of controlling a catalytic cracking unit, the method comprising the steps of:
s1, determining controlled variables in the catalytic cracking unit, wherein the controlled variables are cyclone temperature and regenerator coke content;
s2, obtaining optimal set values corresponding to the cyclone temperature and the regenerator coke content based on a parameterized mathematical model of the catalytic cracking unit;
s3, acquiring a data set of an input variable and an output variable, establishing a prediction model of the coke content of the regenerator, and performing online prediction on the coke content of the regenerator;
and S4, performing online closed-loop control on the cyclone temperature and the output of the software measurement model of the regenerator coke content by using a feedback controller.
Preferably, in step S2, the optimum coke content setting C for the regenerator is setrc,spThe calculation method of (c) is as follows:
s21, setting the variation range of the relevant process parameters, and randomly sampling to obtain N groups of data;
s22, based on the parameterized mathematical model, carrying out optimization solution on economic indexes of each group of data by using a numerical optimization algorithm to obtain group optimal values of coke contents of N groups of regenerators;
s23, taking the average value of the group optimal values of the coke content of the regenerators in the N groups, wherein the average value is the optimal set value Crc,sp；
Wherein N is a positive integer greater than 0.
Preferably, in step S21, the relevant process parameters include a gas-oil cracking reaction parameter k0Coke production constant kcCombustion parameter kcomTemperature sensitivity coefficient sigma of regenerator2First empirical parameter h1A second empirical parameter h2And combustion reaction activation energy Ecb。
Preferably, the related process parameter [ k ]0kckcomσ2h1h2Ecb]Has a variation range of [9620000.0189729.3380.006244521150245158.6 ]]+/-) of20% and N is 1000.
Preferably, step S3 includes the steps of:
s31, selecting the air mass flow FaRegenerated catalyst mass flow rate FscRegenerator temperature TrgAnd riser outlet temperature Tri1Regenerator coke content C as the input variable for a soft measurement modelrcIs the output variable;
s32, acquiring data sets of the input variables and the output variables based on historical data acquired by the parameterized mathematical model or actual measurement of the catalytic cracking unit;
s33, carrying out normalization preprocessing on the data set to enable the mean value of each input variable and each output variable to be 0 and the variance to be 1;
s34, training and obtaining the coke content C of the regenerator based on the soft measurement technologyrcThe predictive model of (1).
Preferably, the prediction model adopts a radial basis function neural network model.
Preferably, the set value T for the temperature of the cyclone separator is optimalcy,spIs Tcy0- β, wherein Tcy0beta is the backspacing value for the safety limit of the cyclone temperature.
preferably, the value of β is between 3 and 7K.
The technical scheme has the following advantages or beneficial effects: in the control method of the catalytic cracking device, the optimization control structure is taken as a means, the cyclone temperature and the regenerator coke content are selected as controlled variables, a regression model is established by combining a soft measurement technology, the regenerator coke content which is difficult to measure on line is predicted, and the on-line closed-loop control of the controlled variables is realized. The whole method is safe to operate and stable to operate, economic indexes are directly optimized to a great extent, and production benefits are effectively improved.
Drawings
Embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings. The drawings are, however, to be regarded as illustrative and explanatory only and are not restrictive of the scope of the invention.
FIG. 1 is a first schematic flow chart of a method for controlling a catalytic cracking unit according to the present invention;
FIG. 2 is a second schematic flow chart of a method for controlling a catalytic cracking unit according to the present invention;
FIG. 3 is a third schematic flow chart of a control method of a catalytic cracking unit according to the present invention.
Detailed Description
The control method of a catalytic cracking unit according to the present invention will be described in detail with reference to the accompanying drawings and specific examples.
As shown in fig. 1, a method for controlling a catalytic cracking apparatus includes the steps of:
s1, determining controlled variables in the catalytic cracking unit, wherein the controlled variables are cyclone temperature and regenerator coke content;
s2, obtaining optimal set values corresponding to the cyclone separator temperature and the regenerator coke content based on a parameterized mathematical model of the catalytic cracking unit;
s3, acquiring a data set of an input variable and an output variable, establishing a prediction model of the coke content of the regenerator, and performing online prediction on the coke content of the regenerator;
and S4, performing online closed-loop control on the output of the software measurement model of the cyclone temperature and the regenerator coke content by using a feedback controller.
Specifically, in step S1, since the cyclone temperature is a constraint variable for ensuring safe operation of the plant and the regenerator coke content is a key variable for improving the economic efficiency of the plant, the cyclone temperature and the regenerator coke content are used as controlled variables.
Further, as shown in FIG. 2, in step S2, the optimum set value C for the coke content of the regeneratorrc,spThe calculation method of (c) is as follows:
s21, setting the change of the relevant process parameters within a certain range, and randomly sampling to obtain N groups of data;
s22, based on the parameterized mathematical model of the catalytic cracking unit, carrying out optimization solution on economic indexes of each group of data by using a numerical optimization algorithm to obtain a group optimal value of the coke content of N groups of regenerators;
s23, averaging the above N groups of regenerator coke content groups to obtain an average value Crc,sp。
Specifically, in step S21, the relevant process parameters include a gas-oil cracking reaction parameter k0Coke production constant kcCombustion parameter kcomTemperature sensitivity coefficient sigma of regenerator2First empirical parameter h1A second empirical parameter h2And combustion reaction activation energy EcbAnd, N is a positive integer greater than 0. For example, the set variation parameter is [ k ]0kckcomσ2h1h2Ecb]The variation range is [9620000.0189729.3380.006244521150245158.6 ]]Plus or minus 20%, taking N as 1000, and the random sampling method used is Monte Carlo sampling method.
In step S22, the economic indicator J is:
-J＝pglFgl+pgsFgs+pugoFugo-poilFoil
in the above formula, each item represents product yield and raw material cost, respectively, where pgl、pgs、pugoAnd poilRespectively the price of gasoline, the price of light gas, the value of unconverted feedstock and the price of gasoline-oil feedstock, Fgl、Fgs、FugoAnd FoilRespectively gasoline yield, light gas yield, amount of unconverted feedstock and initial feedstock flow. The numerical optimization algorithm used for optimizing the economic indicator J is a Sequential Quadratic Programming (SQP) method.
In step S23, Crc,spThe average of the N sets of optimal values was taken. Preferred is Crc,sp0.47% + -0.047%.
Further, as shown in fig. 3, step S3 includes the steps of:
s31, selecting the air mass flow FaRegenerated catalyst mass flow rate FscRegenerator temperature TrgAnd riser outlet temperature Tri1As a soft measurement modelInput variable of (2), regenerator coke content CrcIs an output variable;
s32, acquiring a data set of input variables and output variables based on a parameterized mathematical model of the catalytic cracking unit or historical data acquired through actual measurement;
s33, carrying out normalization pretreatment on the data set to enable the mean value of each variable to be 0 and the variance to be 1;
s34, training and obtaining the coke content C of the regenerator based on the soft measurement technologyrcPreferably, the prediction model employs a radial basis function neural network.
Further, in step S4, a feedback controller is used to perform online closed-loop control on the output of the soft measurement model of the cyclone temperature and the regenerator coke content, and the obtained result is compared with the optimal set value corresponding to the cyclone temperature and the regenerator coke content in step S2, so as to perform online closed-loop control on the cyclone temperature and the regenerator coke content. Preferably, a dispersion control structure is used, using a regenerated catalyst mass flow rate FscControlling cyclone separator temperature, air mass flow FaControlling regenerator coke content CrcThe controller type is PID.
Further, the model of the catalytic cracking unit is described by the following equation:
Figure BDA0001526727300000051
Figure BDA0001526727300000052
Figure BDA0001526727300000053
Figure BDA0001526727300000054
Figure BDA0001526727300000055
Figure BDA0001526727300000056
φ0＝1-mCrc
Figure BDA0001526727300000057
Figure BDA0001526727300000061
Figure BDA0001526727300000062
Figure BDA0001526727300000063
Figure BDA0001526727300000064
Tcy＝Trg+5555Od
Csc＝Crc+Ccat
Figure BDA0001526727300000065
Figure BDA0001526727300000066
ΔH＝-h1-h2(Trg-960)+0.6(Trg-960)2
σ＝1.1+σ2(Trg-873)
wherein the symbols are as follows:
Figure BDA0001526727300000067
Figure BDA0001526727300000071
the optimum set point for the cyclone temperature is Tcy,sp＝Tcy0- β, wherein Tcy0beta is a back-off value, T, for a safe limit for this temperaturecy0the value of β is set by the process requirement, and is between 0 and 10K, preferably 3 to 7K.
In the control method of the catalytic cracking device, the optimization control structure is taken as a means, the cyclone temperature and the regenerator coke content are selected as controlled variables, a regression model is established by combining a soft measurement technology, the regenerator coke content which is difficult to measure on line is predicted, and the on-line closed-loop control of the controlled variables is realized. The whole method is safe to operate and stable to operate, economic indexes are directly optimized to a great extent, and production benefits are effectively improved.
Various alterations and modifications will no doubt become apparent to those skilled in the art after having read the above description. Therefore, the appended claims should be construed to cover all such variations and modifications as fall within the true spirit and scope of the invention. Any and all equivalent ranges and contents within the scope of the claims should be considered to be within the intent and scope of the present invention.

Claims (7)

1. A method of controlling a catalytic cracking unit, the method comprising the steps of:
s1, determining controlled variables in the catalytic cracking unit, wherein the controlled variables are cyclone temperature and regenerator coke content;
s2, obtaining the optimal set value T corresponding to the cyclone temperature based on the parameterized mathematical model of the catalytic cracking unitcy,spAnd an optimum set value C corresponding to the coke content of the regeneratorrc,sp；
S3, acquiring a data set of an input variable and an output variable, establishing a prediction model of the coke content of the regenerator, and performing online prediction on the coke content of the regenerator, wherein the prediction model adopts a radial basis function neural network model;
and S4, performing online closed-loop control on the cyclone temperature and the output of the software measurement model of the regenerator coke content by using a feedback controller.
2. The method of claim 1, wherein the regenerator coke content optimum set value C is set in step S2rc,spThe calculation method of (c) is as follows:
s21, setting the variation range of the relevant process parameters, and randomly sampling to obtain N groups of data;
s22, based on the parameterized mathematical model, carrying out optimization solution on economic indexes of each group of data by using a numerical optimization algorithm to obtain group optimal values of coke contents of N groups of regenerators;
s23, taking the average value of the group optimal values of the coke content of the regenerators in the N groups, wherein the average value is the optimal set value Crc,sp；
Wherein N is a positive integer greater than 0.
3. The method of claim 2, wherein in step S21, the relevant process parameter includes a gas-oil cracking reaction parameter k0Coke production constant kcCombustion parameter kcomTemperature sensitivity coefficient sigma of regenerator2First empirical parameter h1A second empirical parameter h2And combustion reaction activation energy Ecb。
4. The control method of a catalytic cracking unit according to claim 3, characterized in that the relevant process parameter [ k [ ]0kckcomσ2h1h2Ecb]Has a variation range of [9620000.0189729.3380.006244521150245158.6 ]]Plus or minus 20% of the total amount of the N, and the N is 1000.
5. The control method of a catalytic cracking unit according to claim 1, wherein the step S3 includes the steps of:
s31, selecting the air mass flow FaRegenerated catalyst mass flow rate FscRegenerator temperature TrgAnd riser outlet temperature Tri1Regenerator coke content C as the input variable for a soft measurement modelrcIs the output variable;
s32, acquiring data sets of the input variables and the output variables based on historical data acquired by the parameterized mathematical model or actual measurement of the catalytic cracking unit;
s33, carrying out normalization preprocessing on the data set to enable the mean value of each input variable and each output variable to be 0 and the variance to be 1;
s34, training and obtaining the coke content C of the regenerator based on the soft measurement technologyrcThe predictive model of (1).
6. The method of claim 1, wherein the cyclone temperature is set to the optimum value Tcy,spIs Tcy0- β, wherein Tcy0beta is the backspacing value for the safety limit of the cyclone temperature.
7. the control method of the catalytic cracking unit according to claim 6, wherein β is 3 to 7K.
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